Acetazolamide potentiates the anti-tumor potential of HDACi, MS-275, in neuroblastoma
Bibliographic record
Abstract
BACKGROUND: Neuroblastoma (NB), a tumor of the primitive neural crest, despite aggressive treatment portends a poor long-term survival for patients with advanced high stage NB. New treatment strategies are required. METHODS: We investigated coordinated targeting of essential homeostatic regulatory factors involved in cancer progression, histone deacetylases (HDACs) and carbonic anhydrases (CAs). RESULTS: We evaluated the antitumor potential of the HDAC inhibitor (HDACi), pyridylmethyl-N-{4-[(2-aminophenyl)-carbamoyl]-benzyl}-carbamate (MS-275) in combination with a pan CA inhibitor, acetazolamide (AZ) on NB SH-SY5Y, SK-N-SH and SK-N-BE(2) cells. The key observation was that the combination AZ + MS-275 significantly inhibited growth, induced cell cycle arrest and apoptosis, and reduced migration capacity of NB cell line SH-SY5Y. In addition, this combination significantly inhibited tumor growth in vivo, in a pre-clinical xenograft model. Evidence was obtained for a marked reduction in tumorigenicity and in the expression of mitotic, proliferative, HIF-1α and CAIX. NB xenografts of SH-SY5Y showed a significant increase in apoptosis. CONCLUSION: MS-275 alone at nanomolar concentrations significantly reduced the putative cancer stem cell (CSC) fraction of NB cell lines, SH-SY5Y and SK-N-BE(2), in reference to NT2/D1, a teratocarcinoma cell line, exhibiting a strong stem cell like phenotype in vitro. Whereas stemness genes (OCT4, SOX2 and Nanog) were found to be significantly downregulated after MS-275 treatment, this was further enhanced by AZ co-treatment. The significant reduction in initial tumorigenicity and subsequent abrogation upon serial xenografting suggests potential elimination of the NB CSC fraction. The significant potentiation of MS-275 by AZ is a promising therapeutic approach and one amenable for administration to patients given their current clinical utility.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".